Chatbots have increasingly made their presence in the consumer services space According to McKinsey & Company, retailers need to move quickly to seize the opportunity presented by GenAI as they experiment with technology and realize that it holds great promise for reviving growth. One such area is the chatbot.
While the adoption of traditional chatbots and AI chatbots in the retail sector has become a mainstay, what about the impact of generative AI chatbots in an industry where brands fiercely compete for consumer mind share.
Let’s look at the differentiating value of GenAI chatbots.
Unlike traditional linear (rule-based) chatbots, GenAI chatbots offer the feasibility to integrate recommendation engines thanks to their architecture and data processing abilities.No more generic responses to queries. Take the case of shoppers querying for DIY products to spruce up their homes during the holidays. The GenAI chatbot (through domain-based fine-tuned LLMs meant for specific capabilities) would suggest a list of materials and tools based on the project, age, budget and shopper’s skill level. Shoppers feel valued and understood when they receive ideas that align with their needs. GenAI chatbots with inbuilt recommendation engines enhance personalized experiences.
RAG (Retrieval-augmented generation) optimizes an LLM’s responses by integrating real-time information retrieval capabilities and verifying with an external knowledge source for accuracy, thereby reducing hallucinations that normally occur with standard LLMs. Hence, GenAI chatbots integrated with RAG have the depth as they offer nuanced and accurate recommendations that improve conversion rates.
Advanced contextualized conversations are possible with GenAI chatbots to detect intent for relevant and timely conversations. Long conversations become richer and natural with the context intact. With the benefits of RAG, GenAI chatbots excel at handling a broad range of topics and queries suitable for diverse CX scenarios. Product-related conversations become more responsive and interactive.
“The advanced conversational abilities of gen AI chatbots, powered by natural-language models, can make the smart-shopping assistant a primary shopping channel.” – McKinsey & Company.
Retailers are likely to see a spike in engagement levels as GenAI chatbots engage shoppers early on during the cycle. They handle common and repetitive queries and engineers are freed up from monotonous administrative tasks to focus on complex cases. The 24×7 fail-safe assistance ensures high service and satisfaction levels.
GenAI chatbots have become indispensable for garnering shopper’s post-purchase feedback. Primary methods include:
- Conversation surveys (instead of traditional forms) that ask, “Hope you’ve had a good shopping experience, anything else I can help with?”
- Automated follow ups that send feedback forms to find out various aspects of the shopping experience right after the purchase.
- Live-feedback collection that rates shopper experience after the chat.
- Incentivized feedback offers special deals and discounts to encourage shoppers’ responses, and brand engagement.
- Sentiment analysis looks for negative experiences and escalates to human support for follow-ups and resolutions.
With RAG integrated, GenAI chatbots continually learn from shopper interactions and feedback. The continuous and dynamic self-learning mechanisms (real-time, feedback loops, lifelong learning, incremental learning) mean the chatbot evolves with experiences, adjusts to latest information in a dynamic fashion, and enhances performance over time.
Streamlining return processes: The product returns or RMA (Return Merchandise Authorization) space demands an end-to-end capture of the sales process. As most customers prefer to resolve issues by themselves, GenAI chatbots empower self-service options by automating the processes when the customer initiates a return, refund, needs to know the return policies, tracking of orders, and status of returns. GenAI’s summarization capabilities trace customers’ history and provide a detailed footprint revealing key touch points across channels. Engineers have complete visibility (access to chat histories, satisfaction levels, multiple interactions) as to why customers have problems with their orders and they can proactively intervene and resolve the issue.
GenAI chatbot investments mandate a commitment to ethical AI practices and hence retailers looking to leverage the technology need to consider GenAI risk guidelines, safety testing, data protection and regulatory compliance for successful implementation.
Top retailers are updating their customer support assistants with GenAI features aimed at simplifying customer service processes as the ‘standard search bar’ is no longer the quickest route to a purchase.
ISG recognized Movate as a global CX leader in revolutionizing customer journeys with GenAI and digital solutions. Leverage Movate’s suite of IT and digital services to fuel your retail transformation journey. Contact us.
References
- Generative AI in retail: LLM to ROI | McKinsey
- Walmart Reveals How Gen AI and Augmented Reality Are Changing Shopping
- Blog | YourGPT
- RAG in Customer Service Chatbots – Kommunicate.io
- Amazon’s gen AI personalizes product recommendations and descriptions
- How AI-Powered Chatbots are Transforming the Retail Industry – Kore AI
- Using AI to improve customer service — Retail Technology Innovation Hub
- 5 Ways Gen AI is Transforming Retail – ANSR.com
- Reimagine Customer Service with Retail GenAI | Manhattan
- How GenAI Is Changing Retail | Oracle Sénégal
Related information
- Blog: Phygital CX: An imperative for the store of the future
- Blog: Unveiling the power of digital twins
- Web: Retail, CPG and E-commerce: Drive Digital Innovation with Movate
- Case Study: How to Increase Basket Size: The Key to E-commerce Success – Movate
With over 20 years of ITO experience, Amardeep brings a wealth of knowledge in sales, business strategy, business development, and successful direct & indirect sales management. He has held numerous leadership positions during his successful 18-year stint at HCL Tech, out of which, for 15 years he was in Europe, with a proven track record of success in leading teams, particularly in complex sales functions.
Amardeep’s academic background traces its roots back to IT. Beyond his corporate responsibilities, he is an avid blogger, speaker, and technology enthusiast who loves reading, and watching and playing cricket. He champions DEI (diversity, equity, and inclusion) and has notably been associated with Prince’s Trust.
Contact him at amardeep.juneja@movate.com or check out his LinkedIn profile.